Nature can inspire us to explore emerging models of interaction that will help to better understand patterns of collective intelligence in human groups. Steven Johnson, in his book “Emerging Systems” (2001), masterfully demonstrates how that connection (called Biomimicry or biomimetics) is full of metaphors. The Web Ask Nature, the Biomimicry Institute, brings together hundreds of examples of such associations.

In a previous post I mentioned that one of the things I liked about the Collective Intelligence Conference held at MIT in April 2012 was to listen to Deborah Gordon (Stanford) and Ian Couzin (Princeton), two behavioral biologists, who focused on the study of the patterns of behavior of animals in their natural habitats. They are not “biologists” in its classical sense but work as multidisciplinary groups that are making increasing use of mathematics and computer science as well as tracking and geolocation devices to investigate the collective behavior of swarms or “Swarm Intelligence“, a branch of artificial intelligence based on the collective behavior of decentralized and self-organized systems.

Gordon studies the system of foraging in ant colonies in the U.S. and Argentina as a model for analysis of complex collective interactions. While Couzin has chosen fish to test on a small scale hypotheses related to group dynamics. I was fascinated with the experiment that Couzin explained at the conference, which I will review in another post.

The examples provided by these researchers should be examined carefully before trying to extrapolate to human communities. No doubt we are much more complex than other species. But the fact that an ant, a grasshopper or a cricket is far less intelligent than a human can explain that they have a need to unite and seek mechanisms to increase intelligence of the group as a community. People are on the opposite side believing that individual intelligence is enough to make things go well as species, and who knows if this can be a fatal error.

Mankind is so intelligent at individual level that adds too much complexity to the system, so it is likely that the only way to find a socially optimal equilibrium is coming to agreement about “simple rules” of collaboration. The funny thing is that many of these “simple rules” are optimized in nature, and are often manifested through the mechanisms of signal detection that allows so-called social insects coordinate with each other in a more demanding tasks than those permit their individual talents.

In some animals the signals they need to make decisions are not detected individually but through collective aggregation. In the case of ants, they only need local information, the information that each ant has at its disposal, to optimize the performance of the colony. So unravel the complexity of these systems probably provides alternative metaphors to the central control in humans.

What I mean is that these stories-of-biology are much more than thatbecause they are full of social metaphors from which we can learn and should be used to think out-of-the-box, something that we really need.

These swarms act together in a surprisingly coordinated way, developing an intelligence of the group that emerges from an optimization of synergies. Yeah, okay, I understand that it can be a little scary but… there are many gray areas yet to be explored between the extreme selfishness of homo economicus that capitalism uses to “solve” almost everything and the other radical option of forced collectivism of totalitarian regimes.

And I say more. When we are warned that the behavior of animals is too collectivist, and therefore its application to humans would reduce individual creativity, one wonders if there are certain types of challenges that require more social coordination than masturbatory improvisation. There have, for example, the notion of the commons, which seems to me a point of view that responds well to many of the problems that collective human colonies face.

Searching through the Internet I found the Nelson Piedra’s blog, talking about these issues with sufficient criteria. I end this post citing what he says about what he has learned from the so-called “social insects”, because I find it really interesting:

“I envy the insects because of their communal talent. I have tried several times to replicate the model in the initiatives that are in my power: entrepreneurs, research groups, teaching and teamwork. I’m happy with what I got but I know I can improve if I understand the keys to its operation. In this sense, there are three aspects that make social insects so effective: 1) Flexibility: the colony can adapt to a changing environment, extreme, adverse, because it has ability to self-recover, 2) Robustness: when one or more individuals fail, make mistakes or die, the group can still run the task, 3 ) Self-organization: the activities are not controlled centrally or locally monitored (…) Overall the complex sciences, and in particular swarm intelligence has determined that if an individual follows simple rules, the resulting group behavior can be surprisingly complex and highly effective. The flexibility and robustness are the result of self-organization“.

I promise to continue studying nature to explore new metaphors and applications relevant to the Collective Intelligence.

Note-1: The image of the post belongs to the album of luisus_d in Flickr.